IEEE

Autoencoder-Based Analog Fountain Codes for Short Packet Communications

Abstract: Short packet transmission is crucial for ultra-reliable and low-latency communications (URLLC), yet designing efficient channel codes for such scenarios remains challenging due to the ...
Phys.org

Scientists use string theory to crack the code of natural networks

For more than a century, scientists have wondered why physical structures like blood vessels, neurons, tree branches, and other biological networks look the way they do. The prevailing theory held ...
Hosted on MSN

Neural network Python from scratch with softmax

Implement Neural Network in Python from Scratch ! In this video, we will implement MultClass Classification with Softmax by making a Neural Network in Python from Scratch. We will not use any build in ...
IEEE

XAI Driven Software Defect Prediction Using Adaptive Feature Engineering Coupled With Autoencoder and Multi-Layer Perceptron: An Empirical Study

Abstract: Software defect prediction is essential for ensuring the reliability and robustness of software prototypes during development. The current study has proposed a novel strategy that integrates ...
GitHub

Source code for a neural network-based framework for signal separation in spatio-temporal gravity data

B. Heller-Kaikov, R. Pail and M. Werner, Neural network-based framework for signal separation in spatio-temporal gravity data. Computers and Geosciences (2025), doi ...
The New York Times

Cache of Devices Capable of Crashing Cell Network Is Found Near U.N.

The Secret Service discovered more than 100,000 SIM cards and 300 servers, which could disable cellular towers or be used to conduct surveillance. By Eileen Sullivan Reporting from Washington The ...
Frontiers

NESTML: a generic modeling language and code generation tool for the simulation of spiking neural networks with advanced plasticity rules

With increasing model complexity, models are typically re-used and evolved rather than starting from scratch. There is also a growing challenge in ensuring that these models can seamlessly work across ...
gc.cuny

Programming Neural Networks in Python: Part II (continued)

The series is designed as an accessible introduction for individuals with minimal programming background who wish to develop practical skills in implementing neural networks from first principles and ...